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Mapping the Zone: Improving Flood Map Accuracy 5 Coastal Flooding A primary objective of coastal flood studies is to predict the extent and force of floodwaters over land. Because of sparse empirical records and the statistical rarity of extreme coastal events, coastal flood prediction relies on complex numerical models that approximate the processes and phenomena that lead to coastal floods. The predictions yield base flood elevations (BFEs) and spatial areas of flood hazard, which are presented on the Federal Emergency Management Agency’s (FEMA’s) coastal flood maps. This chapter reviews the methodology of coastal flood mapping. The focus is on hurricane-induced flooding, which is responsible for all the major aspects of coastal flooding, including storm surge, heavy rain, and overflowing rivers. The committee did not undertake a set of detailed case studies of coastal flood mapping, nor is it possible to obtain lower bound estimates of flood map accuracy by analysis of stage height records as was done for riverine flooding (Chapter 4). Coastal flood mapping differs from inland flood mapping in several ways. First, there is much greater dependence on simulation models in coastal mapping along with less ability to make inferences from historical gage records as for inland mapping. In riverine flooding, the floodwaters flow down the river system past a succession of stream gages so the maximum discharge and water surface elevation are recorded at many locations. In coastal flooding, the storm comes onshore in a direction transverse to the line of tide gages along the coast. Indeed, no tide gage may be located at the point of maximum effect of a coastal storm. Second, the methodology for coastal flood mapping evolved significantly following hurricanes Katrina and Rita in 2005, and during the Map Modernization Program FEMA was expanding and significantly modifying its guidance documents on coastal flood mapping. The end result is that coastal flood mapping is much more complex and uncertain than riverine flood mapping, and its accuracy is less able to be characterized quantitatively. Accordingly, this chapter presents a survey of coastal flood mapping methodologies and the committee’s assessment of the effectiveness of alternative approaches. FLOOD HAZARDS IN COASTAL SYSTEMS Coastal flood hazards arise from wave and surge dynamics that originate in the ocean and subsequently interact with bathymetric and topographic features on the ocean bottom and land surface (Figure 5.1), respectively. Coastal flood models must account for these features throughout the coastal zone as well as processes associated with the storm surge and waves that create the flood hazard (FEMA, 2006b). Bathymetry and topography change constantly as a result of storms and erosion, and also vary geographically. These geographic differences affect BFEs and result in different coastal flooding responses and flood hazard areas. For example, the Pacific coast is characterized by steep bathymetry and narrow coastal shelves, and flooding is dominated by waves rushing up the shore (wave runup). In contrast, the Atlantic and Gulf coasts are characterized by wide, shallow coastal shelves, and flooding is dominated by storm surge and breaking waves. Erosion continually
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Mapping the Zone: Improving Flood Map Accuracy FIGURE 5.1 Onshore features that affect the propagation of waves, flood insurance rate zones (V and A zones), and base flood elevations. The 100-year stillwater elevation is the water level with a 1 percent annual chance of being exceeded in a given year. SOURCE: FEMA (2003). or episodically changes the ground surface and complicates flood hazard mapping, especially along the Atlantic coast, which has dunes that are reshaped by storms, and, to a lesser degree, the Gulf coast. Storm surge, tides, and waves are the greatest contributors to coastal flooding. Storm surge is the pulse of water that washes onto shore during a storm, measured as the difference between the height of the storm tide and the predicted astronomical tide. It is driven by wind and the inverse barometric effect of low atmospheric pressure, and is influenced by tides and by uneven bathymetric and topographic surfaces. Faster wind speeds and larger storms create a greater storm surge potential. Storm surge alters topographic features that might otherwise dampen the effects of surge and wave forces. For example, sand dunes that normally prevent storm water progress onto a barrier island may be reshaped or even removed during a severe storm. Water surface elevations at the shoreline are a combination of the average water level determined by wind setup (due to the direct action of wind stresses at the air-sea interface) and wave setup (due to breaking waves, Figure 5.2) and a fluctuating water level caused by wave runup (the maximum extent of high-velocity uprush of individual waves above the average water level). All of these factors are included in coastal flood models to estimate the BFE. FEMA COASTAL FLOOD MODELING METHODOLOGY The Basic Structure of Current Coastal Flood Models Coastal flood models estimate BFEs using empirical and probabilistic input data and two modeling steps (Figure 5.3 and Table 5.1): Storm surge models are often loosely coupled with wave models to calculate the 1 percent annual chance stillwater elevation (SWEL) and the wave dynamics associated with a coastal flooding event. Recent flood studies in Mississippi and Louisiana used loosely coupled two-dimensional (2-D) surge and wave models to calculate the SWEL and wave setup. The SWEL value (with or without wave setup) from the wave and surge models is used to calculate wave crest values using erosion and wave calculations through the Coastal Hazards Analysis and Modeling Program (CHAMP) and the Wave Height Analysis
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Mapping the Zone: Improving Flood Map Accuracy FIGURE 5.2 Schematic of wave setup (η; rise in the water surface caused by breaking waves of height H) and wave runup (R(t); the rush of wave water up a slope or structure). Wave setup and wave runup raise water elevations above the stillwater level (SWL). SOURCE: U.S. Geological Survey, <http://coastal.er.usgs.gov/hurricanes/impact-scale/water-level.html#runup>. for Flood Insurance Studies (WHAFIS) program. The recent Mississippi study used the SWEL and wave setup calculated by the Advanced Circulation (ADCIRC) and Simulating WAves Nearshore (SWAN) models to calculate the wave crest in CHAMP. The wave crest is combined with the SWEL and wave setup to yield the BFE. Depending on the region, wave runup and overtopping may have to be calculated and added to the wave crest. Evolution of Coastal Flood Models and Mapping Prior to 1975, coastal BFEs for Flood Insurance Rate Maps (FIRMs) were calculated using limited historical records and an early storm surge model, but without consideration of waves. In the late 1970s, FEMA supported the development of a 2-D storm surge model (FEMASURGE) for calculating the SWEL caused by storm surge, again without consideration of wave effects on the storm surge or BFEs. These early models used simplified assumptions, coarse grid resolutions, and a simple parametric hurricane model to minimize computational effort. In 1977, FEMA asked the National Research Council (NRC) to determine how to incorporate calculations of wave height and runup in flood map projects for Atlantic and Gulf coast communities. The NRC (1977) concluded that wave height predictions should be included in coastal flood mapping and provided a methodology to account for varying fetch lengths (length of water over which a given wind has blown), barriers to wave transmission, and regeneration of waves likely to occur over flooded land areas. Based on the NRC (1977) recommendations, FEMA developed WHAFIS to provide wave heights for the BFEs. FEMA has also made many incremental improvements in probabilistic methods for selecting an ensemble of hurricane and storm parameters and return periods; storm surge modeling; and calculation of wave setup, wave runup, wave crest, erosion, and the effects of structures on surge and waves. For example, the Joint Probability Method (JPM), introduced in 1981, was used to determine the hurricane ensemble and return period in coastal regions based on available hurricane data and statistical properties of hurricane wind parameters at landfall. The catastrophic flooding in Louisiana and Mississippi during Hurricane Katrina in 2005 triggered new interest in developing more advanced models. JPM has been improved, and the Interagency Performance Evaluation Task Force
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Mapping the Zone: Improving Flood Map Accuracy FIGURE 5.3 Current FEMA coastal mapping procedures used in Mississippi and Louisiana. In these studies, two-dimensional surge (ADCIRC) and wave (SWAN for Mississippi and STeady State spectral wave [STWAVE] for Louisiana) models are used to calculate the 1 percent annual chance stillwater elevation, and CHAMP/WHAFIS is used to calculate overland wave crest and post-storm topography. The 1 percent annual chance SWEL and the wave crest are then combined to calculate the BFE. NOTE: FIRM = Flood Insurance Rate Map. TABLE 5.1 Elements of FEMA’s Current Coastal Flood Mapping Process Empirical and Probabilistic Input Data Coupled Surge and Wave Models for SWEL Calculation Wave Crest and BFE Calculation Hurricane data Probabilistic hurricane wind model data Hurricane ensemble and return period data Bathymetric data Pre- and post-storm topographic data 2-D storm surge model 2-D wave model CHAMP/WHAFIS erosion and wave calculations along one-dimensional (1-D) transects Post-storm topographic data to verify CHAMP/WHAFIS results
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Mapping the Zone: Improving Flood Map Accuracy (IPET, 2008) developed the JPM-OS (Optimal Sampling) method to reduce the number of hurricanes in the hurricane ensemble. The Empirical Simulation Technique (EST), was developed to reduce the computational burden by considering only the combinations of storm characteristics that have been observed in the historical record. A comparison of the JPM and EST methods appears in Divoky and Resio (2008). A new generation of storm surge and wave models is now being used for flood mapping in Mississippi, Louisiana, Texas, and North Carolina and will be used in other states in the future. FEMA’s guidelines for coastal flood mapping have also evolved.1 Policies and procedures were established for storm surge modeling by 1985 and for wave and V zone modeling by 1995. Updates in coastal modeling guidance accelerated in 2002. Separate guidance has been developed for the Atlantic and Gulf coasts, the Pacific coast, and sheltered coastlines. Yet even with these updates, the recent switch to coupled storm surge-wave modeling for flood map production is still “beyond the scope of these guidelines” (FEMA, 2007a), and mapping contractors are referred to the specific user’s manual for each model. FEMA is currently working with individual mapping contractors to implement the models in flood map production. Wave Height Analysis for Flood Insurance Studies (WHAFIS) WHAFIS analyzes wave effects along one-dimensional (1-D) transects normal to the shore (Figure 5.4) to determine the wave height. The relatively simple 1-D method was originally recommended because wave transformation processes in shallow water were not well understood, and robust 2-D wave models and the computational power to run them did not exist (NRC, 1977). Patches added to the original WHAFIS program since 1989 include methods to calculate wave height elevations above the storm surge elevation and wave setup along 1-D transects. The improved WHAFIS was combined with patches for calculating wave runup and storm-induced dune erosion along 1-D transects into a new software package, CHAMP. The results are then interpolated to produce the wave crest over a 2-D onshore environment. Wave crests calculated by CHAMP/WHAFIS have not been sufficiently validated, creating potentially significant uncertainties in BFE estimates. Factors that contribute to the uncertainty of WHAFIS wave crest calculations include the following (Sheng and Alymov, 2002): Wave transformation is a 2-D process that cannot be represented in a 1-D model. WHAFIS wave crests and BFEs are not 1 percent annual chance values (i.e., probabilistic wave conditions are not incorporated in the WHAFIS calculations). Surge and wave are completely decoupled, which may lead to over- or underestimates of the BFE. The 540-square-foot rule for dune erosion (i.e., a dune exceeding a cross-sectional area of 540 square feet will not be breached in a 1 percent annual chance storm) has not been validated. The approach for wave dissipation by vegetation, buildings, and levees has not been validated. One-dimensional transects do not reflect 2-D terrain. Manual interpolation of 1-D results to two dimensions is subjective. Despite these known limitations, WHAFIS has been the wave analysis method recommended by FEMA since 1989. A number of 2-D models have been developed, and studies demonstrate that coupled 2-D models are at least as accurate as WHAFIS and in most cases are better at representing the fullness of wind wave crest and storm surge dynamics in coastal flood zones (e.g., Sheng and Alymov, 2002). The current 2-D coupled surge and wave models use probabilistic methods, whereas WHAFIS determines wave crest elevation on top of the SWEL along 1-D transects. Which modeling approach yields more uncertainty in the BFE value has not been studied. FEMA Coastal Flood Modeling in the Post-Katrina Era Since Hurricane Katrina in 2005, FEMA has encouraged rapid advancements in coastal flood modeling and mapping. Improvements currently under way 1 See description and references at <http://www.fema.gov/plan/prevent/fhm/dl_vzn.shtm#1>.
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Mapping the Zone: Improving Flood Map Accuracy FIGURE 5.4 Aerial photograph of the coast near Biloxi, Mississippi, showing the layout of one-dimensional WHAFIS transects (red lines). SOURCE: Courtesy of David Divoky, HSMM/AECOM. Used with permission. include development of better hurricane ensemble parameters, more accurate estimates of the return period of storms in several coastal regions, more accurate simulations of storms surge and estimations of SWEL in Louisiana and Mississippi, and increased use of very fine, unstructured grids (100 meters or less) to resolve complex coastal terrains and enable the use of high-resolution lidar (light detection and ranging) data. FEMA (2006b) recommended merging developments in hydrodynamic and statistical methods with established methods for wave analysis, erosion assessment, and flood hazard mapping. However, coupled 2-D surge and wave models are not yet fully integrated into mapping practice because 2-D wave models “do not incorporate bottom friction and obstruction effects of the sort considered by WHAFIS” and FEMA has not developed guidelines for 2-D overland wave modeling (FEMA, 2008b). Recent applications of coupled 2-D surge and wave models have demonstrated their ability to calculate wave setup and wave crest (Sheng and Alymov, 2002; IPET, 2008). In Louisiana, Mississippi, and North Carolina, novel approaches to coastal flood mapping are either under way or have recently been completed. These new coastal mapping studies are the first to replace FEMASURGE with the ADCIRC model and could be used as part of a more comprehensive assessment of methods for enhancing mapping—for example, by gathering more data for verifying wind, storm surge, and wave models (see below). FROM MODELS TO MAPS: DEVELOPING THE NEXT GENERATION OF COASTAL FLOOD MODELS Coastal flood models—and by extension, coastal flood maps—will continue to be improved in the coming decades, driven by the increased availability of high-resolution topographic data and more sophisticated models. This section identifies opportunities to improve the accuracy of coastal flood models and recommends ways to guide the development of the next generation of coastal flood models and maps.
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Mapping the Zone: Improving Flood Map Accuracy Decreasing Uncertainty in Coastal Flood Models The BFE is a key variable used to define flood hazard areas on coastal FIRMs. However, it is the final output of the models and reflects uncertainties in the input data and every stage of the modeling process. Major sources of uncertainty include calculation of the SWEL using a 2-D surge model and the nonprobabilistic wave crest using a 1-D WHAFIS model, use of coarse grid resolution and small model domain, use of simple and empirical procedures or models to represent the effect of topographic features on surge and waves, quantification of hurricane return period and ensemble, exaggerated wind conditions (e.g., 80 miles per hour blowing perpendicular to shore), unrealistic wave boundary conditions at the shore, and topographic and bathymetric data. Sources of uncertainty in storm surge and wave models are shown in Figure 5.5. The impact of uncertainties in these factors on the accuracy of calculated storm surge and coastal inundation has not been examined, but may need to be quantified to make significant improvements in coastal models and maps. The sensitivity and uncertainty of simulated storm surge and inundation to these factors is beginning to be examined in regional test beds, such as the one described in Box 5.1. Considerable differences exist among the available storm surge models in terms of model dimensionality, grid resolution, efficiency, and processes modeled. Increasing model grid resolution in the coastal region improves the model’s ability to resolve local and geometric features and increases the accuracy of simulated surge. Increasing the size of the coastal domain enables modelers to simulate hurricane effects further from shore, reducing uncertainty in surge and wave water levels. However, both the increased resolution and the increased domain size add to the computational time of the simulations. Added computational resources enabled recent coastal flood studies in Mississippi and Louisiana to use much higher resolution and larger coastal domains than have traditionally been used for these types of studies (e.g., IPET, 2008). More efficient surge and wave models would reduce computation costs. The accuracy of simulated storm surge and waves is sensitive to the way wave-current interaction is parameterized in the model, including the wave-enhanced drag coefficient, radiation stress, and wave-current bottom friction. Recommendation. FEMA should work with other federal agencies and academic institutions to develop a test bed to assess and compare the various models used for coastal flood mapping. As a start, FEMA should compare the flood maps for the New Orleans region produced by IPET using coupled 2-D surge and wave models with those produced by FEMA using a 2-D surge model and a 1-D wave model. More Robust 2-D and 3-DModels Storm surge has been simulated using 1-D, 2-D, and three-dimensional (3-D) models, although 1-D models have known shortcomings. After Hurricane Katrina, FEMA accelerated the improvement of coastal modeling methodology by adopting the more advanced 2-D surge model ADCIRC and the 2-D wave model SWAN. Although FEMA has not fully embraced the use of coupled 2-D surge and wave models to calculate BFEs and wave crests, the successful use of this method by the Interagency Performance Evaluation Task Force increases the likelihood that 2-D methods will eventually replace the current 2-D (wave and surge models) plus 1-D (WHAFIS/CHAMP) method. Recommendation. FEMA should use coupled 2-D surge and wave models to reduce uncertainties associated with the use of a 2-D surge model and the 1-D WHAFIS model. Before choosing which models to incorporate into mapping practice, an analysis of the impact of various uncertainties on the models should be undertaken. Sometimes even 2-D models cannot represent the full range of physical processes involved. For example, marshes, barrier islands, buildings, dunes, and levees resist storm surge and waves, and hence can significantly affect the surge, wave heights, and inundation. These 3-D processes are not adequately resolved in FEMA-approved 2-D storm surge models and may require 3-D modeling. Another example concerns flow-structure interaction, which has a significant effect on flooding in some regions. Even when the SWEL is below the height of a coastal barrier (e.g., a levee or large dune), the topographic feature may be overtopped and/or eroded. If these processes are not included in the models, flooding and waves in the land
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Mapping the Zone: Improving Flood Map Accuracy FIGURE 5.5 Sources of uncertainties associated with storm surge and wave modeling. Although every item in this figure contributes to the overall uncertainty of the simulated storm surge and waves and the calculated 1 percent annual chance flood elevation, their relative contributions are not well understood because a systematic uncertainty analysis has not been done. area and bays behind the topographic features could be underestimated. Hence, it is important to incorporate the effect of topographic features on coastal flooding in 2-D or 3-D storm surge and wave models, as appropriate. In addition to developing new capabilities, the next generation of coastal flood models can take better advantage of the capabilities of existing 2-D and 3-D models. For example, 2-D wave models already in use with storm surge models represent a significant
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Mapping the Zone: Improving Flood Map Accuracy BOX 5.1 Coastal Mapping Test Bed Over the last few years, flood mapping along the Atlantic and Gulf coasts has shifted from locally applied storm surge models to the regionally applied ADCIRC model coupled with the SWAN wave model as maps are updated. FEMA has also authorized the use of other storm surge models. These models were typically developed independently from university research efforts. Each model has its own strengths, weaknesses, and data needs. However, there have been little direct comparisons of the models and limited testing to optimize computational efficiency and data needs. An effective way to compare the accuracy and/or efficiency of different models and to optimize the data requirements is to develop a model test bed. One such test bed is being developed under a grant from the National Oceanic and Atmospheric Administration’s (NOAA’s) Integrated Ocean Observing System Program through the Southeast Coastal Ocean Observing Regional Association. The test bed consists of four modeling groups, including the University of Florida (CH3D-SSMS modeling system), the University of North Carolina (ADCIRC model), the University of South Florida (FVCOM), and North Carolina State University (CEMAS based on POM), plus participants from NOAA, FEMA, the U.S. Army Corps of Engineers (USACE), the U.S. Geological Survey, the Florida Department of Emergency Management, the North Carolina Division of Emergency Management, the Northeast Florida Regional Planning Council, Broward County, Florida, and URS Corporation. High-resolution topographic and bathymetric data along the southeastern coasts as well as historical storm data will be collected and analyzed for verification of the four academic models and the NOAA SLOSH model. After verification, the models will be used to determine how different model features or attributes will affect model accuracy and efficiency, and how model parameters and options such as grid density and time steps can be varied to optimize modeling accuracy and efficiency. The different models will be used to produce storm surge atlases (similar to the SLOSH maps) and prototype FIRMs, and these products will be compared to determine how sensitive they are to different model features and attributes. The test bed will be complete by the end of 2010. SOURCE: <http://ioos.coastal.ufl.edu/>, <http://ioos.noaa.gov/>. improvement over WHAFIS. These changes, illustrated in Figure 5.6, would significantly advance FEMA’s coastal models by yielding more accurate estimates of the SWEL, wave crest, and BFE. Recommendation. FEMA should work toward a capability to use coupled surge-wave-structure models to calculate base flood elevations, starting with incorporating coupled two-dimensional surge and wave models into mapping practice. Post-storm Topographic Data Topographic data following a 1 percent annual chance or more severe storm is becoming increasingly available in some coastal areas. Post-hurricane Katrina and Rita topographic data were used in Louisiana and Mississippi to validate the existing levee overtopping-erosion model (IPET, 2008). These data could also be used to develop and validate more robust storm surge and wave models in the future. Precedence for collecting post-storm topography during most of the recent storms has been set and should become the new standard practice. Recommendation. FEMA should expand collection of high-resolution topographic data to all coastal counties and require collection of post-storm topographic data to validate storm surge and wave models and improve their accuracy. Bathymetric Data Accurate bathymetry is a prerequisite for accurate simulation of storm surge, waves, and coastal flooding. Since storm surge and waves propagate over a long distance before landfall, it is necessary to have accurate bathymetry for both the offshore (greater than 20-meter depth) and the nearshore (less than 20-meter depth) regions. Currently available bathymetric data are often outdated, particularly far from shore where the data may be decades old. However, updating bathymetric data is costly. Given limited funding, priority should be given to bathymetric surveys in the nearshore region where high surge and waves develop and affect coastal communities. Nonlinear wave models have shown that infragravity waves (waves with a period of 20 to 300 seconds) are created by wave-bathymetry interactions at depths of 15 to 20 meters
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Mapping the Zone: Improving Flood Map Accuracy FIGURE 5.6 Recommended coastal flood modeling and mapping procedures for FEMA. Coupled surge-wave-structure models allow calculation of 1 percent annual chance SWEL, wave setup, wave crest, and BFE simultaneously. Enhanced “structure” models account for surface roughness, erosion, and overtopping or failure of topographic features. In the interim, the committee recommends using post-storm topography and new data to develop or validate the “structure” models and to validate the CHAMP/WHAFIS erosion-wave calculations and using fully coupled surge-wave models for SWEL and wave crest calculations. and shallower. The extent to which perturbations in the bathymetry affect storm surges or waves modeled using FEMA’s flood mapping methods is unknown, although preliminary tests suggest that surge and waves are more sensitive to nearshore bathymetry than to offshore bathymetry. Recommendation. FEMA should work with NOAA and the USACE to acquire high-accuracy bathymetric data in coastal, estuarine, and riverine areas. A Comprehensive Coastal Flood Mapping Uncertainty Study FEMA has overseen many incremental improvements to the basic CHAMP/WHAFIS model structure. Some of the patches contain simplifying assumptions that could increase uncertainty in the calculated BFE. The uncertainties associated with these patches, however, have never been assessed quantitatively. Similarly, the research community has been creating increasingly
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Mapping the Zone: Improving Flood Map Accuracy sophisticated 2-D and 3-D models for surge, waves, and other coastal phenomena (e.g., Sheng and Alymov, 2002; IPET, 2008). Whether any of these new models would improve FEMA’s modeling process is just beginning to be assessed in test beds. For example, the test bed led by the University of Florida is comparing four research storm surge and inundation models as well as the flood maps produced using the models.2 A comprehensive uncertainty study could help identify opportunities to increase the accuracy of coastal flood studies and priorities for improving FEMA’s coastal flood modeling and mapping methods. Recommendation. FEMA should commission an external advisory group to conduct an independent, comprehensive assessment of coastal flood models to identify ways to reduce uncertainties in the models and to improve the accuracy of BFEs. Such an assessment could consider factors such as Performance metrics and standards for storm surge models and wind fields, The necessary size of the coastal domain for storm surge simulation, The effectiveness of patches applied to the WHAFIS/CHAMP model, and The level of uncertainty associated with current 2-D and 3-D models, probabilistic methods, and WHAFIS. CONCLUSIONS Coastal flood studies rely on models of atmospheric and ocean phenomena that originate far from shore and that change in the nearshore and onshore environment. Considerable progress has been made in modeling these phenomena and mapping coastal flood hazard over the last 30 years. The modeling changes were usually incorporated in the form of patches. Modeling methodology is now poised for a major step forward, enabled by the availability of more advanced models and increased computing power, and sped by the need to better understand and represent coastal flood processes in the wake of Hurricane Katrina. The key to improving coastal flood maps lies in improving the coastal flood models that are used to calculate the BFE, improving estimates of hurricane return period, and gathering more accurate pre- and post-storm topographic data. Published studies comparing WHAFIS with 2-D surge and wave models suggest that coupled 2-D surge and wave models yield more accurate BFEs, and the committee endorses their use. Other models emerging from the research community offer new or enhanced capabilities—such as those for calculating the effect of waves on storm surge and the effect of levees, marshes, or dunes on storm surge and waves—but they have not been compared to one another or to FEMA models to determine whether incorporating them into mapping practice would significantly improve the accuracy of coastal flood maps. A comprehensive model intercomparison study would help focus effort on which models should be further developed and adopted into FEMA methodology. The ultimate goal would be to use coupled models of storm surge, waves, and the effects of surface roughness, erosion, and overtopping or failure of topographic features to calculate the 1 percent annual chance stillwater elevation, wave setup, wave crest, and base flood elevation simultaneously. Similarly, cost comparisons of recent coastal mapping studies in Louisiana, Mississippi, and North Carolina—which were not available at the time of writing of this report—with older studies would help FEMA choose which new models are most cost-effective to pursue. 2 See <http://ioos.coastal.ufl.edu>.
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